Aws. Lesson 2. Dynamodb

DynamoDB Tutorial with 4 Examples per Topic

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1. Creating a Table

Example 1: Basic Table Creation

import boto3

dynamodb = boto3.resource('dynamodb')

table = dynamodb.create_table(
    TableName='Users',
    KeySchema=[{'AttributeName': 'UserID', 'KeyType': 'HASH'}],
    AttributeDefinitions=[{'AttributeName': 'UserID', 'AttributeType': 'S'}],
    ProvisionedThroughput={'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5}
)

print("Table created")

Explanation

1. Connects to DynamoDB using the boto3 library.

   • dynamodb = boto3.resource('dynamodb')

2. Creates a Users table with a primary key.

   • TableName='Users', KeySchema=[{'AttributeName': 'UserID', 'KeyType': 'HASH'}]

3. Defines UserID as a string attribute.

   • AttributeDefinitions=[{'AttributeName': 'UserID', 'AttributeType': 'S'}]

4. Sets read/write capacity at 5 units each.

   • ProvisionedThroughput={'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5}

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Example 2: Creating a Table with Sort Key

table = dynamodb.create_table(
    TableName='Orders',
    KeySchema=[
        {'AttributeName': 'OrderID', 'KeyType': 'HASH'},
        {'AttributeName': 'CustomerID', 'KeyType': 'RANGE'}
    ],
    AttributeDefinitions=[
        {'AttributeName': 'OrderID', 'AttributeType': 'S'},
        {'AttributeName': 'CustomerID', 'AttributeType': 'S'}
    ],
    ProvisionedThroughput={'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5}
)

Explanation

1. Creates an Orders table with a primary and sort key.

   • KeySchema=[{'AttributeName': 'OrderID', 'KeyType': 'HASH'}, {'AttributeName': 'CustomerID', 'KeyType': 'RANGE'}]

2. Defines both keys as string attributes.

   • AttributeDefinitions=[{'AttributeName': 'OrderID', 'AttributeType': 'S'}, {'AttributeName': 'CustomerID', 'AttributeType': 'S'}]

3. Sort key allows querying by CustomerID.

   • KeyType='RANGE'

4. Uses ProvisionedThroughput to control costs.

   • ProvisionedThroughput={'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5}

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Example 3: List Tables

client = boto3.client('dynamodb')
response = client.list_tables()

print(response['TableNames'])

Explanation

1. Uses the DynamoDB client to interact with AWS.

   • client = boto3.client('dynamodb')

2. Retrieves a list of all tables.

   • response = client.list_tables()

3. Prints the table names in the account.

   • print(response['TableNames'])

4. Helps verify available tables before operations.

   • list_tables()

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Example 4: Delete a Table

table = dynamodb.Table('Users')
table.delete()
print("Table deleted")

Explanation

1. Gets a reference to the Users table.

   • table = dynamodb.Table('Users')

2. Calls delete() to remove it.

   • table.delete()

3. Deletes the entire table permanently.

   • delete()

4. Prints a confirmation message.

   • print("Table deleted")

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2. Inserting Data

Example 1: Insert a Single Item

table = dynamodb.Table('Users')

table.put_item(Item={
    'UserID': '123',
    'Name': 'Alice',
    'Email': 'alice@example.com'
})

Explanation

1. Gets a reference to the Users table.

   • table = dynamodb.Table('Users')

2. Calls put_item() to insert a new record.

   • table.put_item(Item={...})

3. Defines the UserID, Name, and Email.

   • 'UserID': '123', 'Name': 'Alice', 'Email': 'alice@example.com'

4. Ensures atomicity for single-item inserts.

   • put_item()

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Example 2: Batch Insert Multiple Items

with table.batch_writer() as batch:
    batch.put_item(Item={'UserID': '124', 'Name': 'Bob'})
    batch.put_item(Item={'UserID': '125', 'Name': 'Charlie'})

Explanation

1. Uses batch_writer() for efficient writes.

   • with table.batch_writer() as batch:

2. Inserts multiple UserID entries in one call.

   • batch.put_item(Item={'UserID': '124', 'Name': 'Bob'})

3. Reduces API call overhead.

   • batch.put_item(Item={'UserID': '125', 'Name': 'Charlie'})

4. Helps when inserting many records quickly.

   • batch_writer()

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Example 3: Insert with Condition

table.put_item(
    Item={'UserID': '126', 'Name': 'Dave'},
    ConditionExpression="attribute_not_exists(UserID)"
)

Explanation

1. Inserts only if UserID does not exist.

   • ConditionExpression="attribute_not_exists(UserID)"

2. Prevents overwriting existing users.

   • put_item(Item={...})

3. Ensures data consistency for unique keys.

   • ConditionExpression

4. Raises an error if UserID exists.

   • attribute_not_exists(UserID)

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Example 4: Insert with Auto Timestamp

import time

table.put_item(Item={
    'UserID': '127',
    'Name': 'Eve',
    'CreatedAt': int(time.time())
})

Explanation

1. Uses time.time() to store timestamps.

   • int(time.time())

2. Ensures each record has a CreatedAt field.

   • 'CreatedAt': int(time.time())

3. Helps track when a record was inserted.

   • CreatedAt

4. Stores timestamps in UNIX format.

   • time.time()

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3. Fetching Data

Example 1: Get a Single Item

response = table.get_item(Key={'UserID': '123'})
print(response.get('Item'))

Explanation

1. Retrieves a record by UserID.

   • table.get_item(Key={'UserID': '123'})

2. Uses get() to avoid key errors.

   • response.get('Item')

3. Prints the retrieved user data.

   • print(response.get('Item'))

4. Returns None if UserID not found.

   • get_item()

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Example 2: Query Data by Sort Key

response = table.query(
    KeyConditionExpression="CustomerID = :cid",
    ExpressionAttributeValues={":cid": "CUST123"}
)

Explanation

1. Queries CustomerID = 'CUST123'.

   • KeyConditionExpression="CustomerID = :cid"

2. Uses ExpressionAttributeValues to pass parameters.

   • ":cid": "CUST123"

3. Returns multiple matching records.

   • table.query()

4. More efficient than scanning the entire table.

   • query()

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